Road Target Search and Tracking with Gimballed Vision Sensor on an Unmanned Aerial Vehicle

Creative Commons License

Skoglar P., Orguner U., Tornqvist D., Gustafsson F.

REMOTE SENSING, cilt.4, sa.7, ss.2076-2111, 2012 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 4 Sayı: 7
  • Basım Tarihi: 2012
  • Doi Numarası: 10.3390/rs4072076
  • Dergi Adı: REMOTE SENSING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2076-2111
  • Anahtar Kelimeler: UAV surveillance, sensor management, path planning, search theory, road target tracking, particle filter, stochastic scheduling, security and monitoring, MOVING TARGET, UAVS, SYSTEMS, TIME
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

This article considers a sensor management problem where a number of road bounded vehicles are monitored by an unmanned aerial vehicle (UAV) with a gimballed vision sensor. The problem is to keep track of all discovered targets and simultaneously search for new targets by controlling the pointing direction of the vision sensor and the motion of the UAV. A planner based on a state-machine is proposed with three different modes; target tracking, known target search, and new target search. A high-level decision maker chooses among these sub-tasks to obtain an overall situational awareness. A utility measure for evaluating the combined search and target tracking performance is also proposed. By using this measure it is possible to evaluate and compare the rewards of updating known targets versus searching for new targets in the same framework. The targets are assumed to be road bounded and the road network information is used both to improve the tracking and sensor management performance. The tracking and search are based on flexible target density representations provided by particle mixtures and deterministic grids.